


"""simple docstring"""



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowercase_							=							{
    'configuration_chinese_clip': [
        'CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'ChineseCLIPConfig',
        'ChineseCLIPOnnxConfig',
        'ChineseCLIPTextConfig',
        'ChineseCLIPVisionConfig',
    ],
    'processing_chinese_clip': ['ChineseCLIPProcessor'],
}

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase_							=							['ChineseCLIPFeatureExtractor']
		lowercase_							=							['ChineseCLIPImageProcessor']

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase_							=							[
		    'CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'ChineseCLIPModel',
		    'ChineseCLIPPreTrainedModel',
		    'ChineseCLIPTextModel',
		    'ChineseCLIPVisionModel',
		]

if TYPE_CHECKING:
		from .configuration_chinese_clip import (
		    CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    ChineseCLIPConfig,
		    ChineseCLIPOnnxConfig,
		    ChineseCLIPTextConfig,
		    ChineseCLIPVisionConfig,
		)
		from .processing_chinese_clip import ChineseCLIPProcessor

		try:
				if not is_vision_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_chinese_clip import ChineseCLIPFeatureExtractor, ChineseCLIPImageProcessor

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_chinese_clip import (
				    CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ChineseCLIPModel,
				    ChineseCLIPPreTrainedModel,
				    ChineseCLIPTextModel,
				    ChineseCLIPVisionModel,
				)

else:
		import sys

		lowercase_							=							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



"""simple docstring"""



from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase_							=							logging.get_logger(__name__)

lowercase_							=							{
    's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}







class    __a						( __snake_case							):
				lowerCamelCase     :       Union[str, Any]			       ='open-llama'







				def __init__( self      ,	UpperCAmelCase=10_0000      ,	UpperCAmelCase=4096      ,	UpperCAmelCase=1_1008      ,	UpperCAmelCase=32      ,	UpperCAmelCase=32      ,	UpperCAmelCase="silu"      ,	UpperCAmelCase=2048      ,	UpperCAmelCase=0.0_2      ,	UpperCAmelCase=1E-6      ,	UpperCAmelCase=True      ,	UpperCAmelCase=0      ,	UpperCAmelCase=1      ,	UpperCAmelCase=2      ,	UpperCAmelCase=False      ,	UpperCAmelCase=True      ,	UpperCAmelCase=0.1      ,	UpperCAmelCase=0.1      ,	UpperCAmelCase=True      ,	UpperCAmelCase=True      ,	UpperCAmelCase=None      ,	**UpperCAmelCase      ,	):

					'''simple docstring'''






					lowerCAmelCase_      							=			vocab_size
					lowerCAmelCase_      							=			max_position_embeddings
					lowerCAmelCase_      							=			hidden_size
					lowerCAmelCase_      							=			intermediate_size
					lowerCAmelCase_      							=			num_hidden_layers
					lowerCAmelCase_      							=			num_attention_heads
					lowerCAmelCase_      							=			hidden_act
					lowerCAmelCase_      							=			initializer_range
					lowerCAmelCase_      							=			rms_norm_eps
					lowerCAmelCase_      							=			use_cache
					lowerCAmelCase_      							=			kwargs.pop(
					    '''use_memorry_efficient_attention'''      ,	UpperCAmelCase   )
					lowerCAmelCase_      							=			hidden_dropout_prob
					lowerCAmelCase_      							=			attention_dropout_prob
					lowerCAmelCase_      							=			use_stable_embedding
					lowerCAmelCase_      							=			shared_input_output_embedding
					lowerCAmelCase_      							=			rope_scaling
					self._rope_scaling_validation()

					super().__init__(
					    pad_token_id=UpperCAmelCase      ,	bos_token_id=UpperCAmelCase      ,	eos_token_id=UpperCAmelCase      ,	tie_word_embeddings=UpperCAmelCase      ,	**UpperCAmelCase      ,	)







				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					if self.rope_scaling is None:
						return

					if not isinstance(self.rope_scaling      ,	UpperCAmelCase   ) or len(self.rope_scaling   ) != 2:
						raise ValueError(
						    '''`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, '''
						    F"""got {self.rope_scaling}"""   )
					lowerCAmelCase_      							=			self.rope_scaling.get('''type'''      ,	UpperCAmelCase   )
					lowerCAmelCase_      							=			self.rope_scaling.get('''factor'''      ,	UpperCAmelCase   )
					if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
						raise ValueError(
						    F"""`rope_scaling`'s name field must be one of ['linear', 'dynamic'], got {rope_scaling_type}"""   )
					if rope_scaling_factor is None or not isinstance(UpperCAmelCase      ,	UpperCAmelCase   ) or rope_scaling_factor <= 1.0:
						raise ValueError(F"""`rope_scaling`'s factor field must be an float > 1, got {rope_scaling_factor}"""   )